The invention relates to a method for forest inventory and the determination of stand attributes. With the aid of the method, stand attributes of trees, sample plots and larger forest areas can be measured by measuring and deriving the most important characteristics of individual trees. The invention also relates to a computer program to carry out the method.
Conventional forest inventory is mostly based on field measurements. E.g. forest inventory at stand level, in which the forest is first divided into almost homogeneous forest units (typically 1-3 hectares in size), is presently based on plot measurements and subjective ocular inventory. Aerial photographs and orthophotos (aerial photos rectified to map projection) are typically used in delineation of stand boundaries and determination of the walking route in the forest However, stand attributes, such as the volume (m3/ha), the basal area (m2/ha, depicts the cross-sectional area per hectare at the height of 1.3 m), mean height (m), other density type characteristics, tree species, age, and development class, are determined by measurements and assessments carried out in forests. This work has been tried to been made more effective by increasing the level of automation, e.g. by field computers and by more automatic measurement equipment (e.g. patent Fl 101016 B). In forest inventory at stand level, tree and stand attributes are calculated by plotwise information carried out in the same stand and by ocular estimation. In addition to standwise forest inventory, plotwise forest inventory, measurements of single trees, and estimation of larger areas, such as whole nations or parts of them, are carried out.
Remote sensing methods (measurement of target properties without any physical contact) have been studied for a long time as an alternative and future method for the traditional field inventory work. At large area forest inventory, promising results have been obtained by using satellite imagery (e.g. Tomppo E. 1991. Satellite image-based national forest inventory of Finland. International Archives of Photogrammetry and Remote Sensing. 28: 419-424). In such methods, field-measured plotwise data are typically used as a teaching data set and the satellite image is used to generalize this carefully corrected field data for the whole image. A prerequisite for a successful solution for small areas is that features (channels, ratio of channels and the like) from the satellite image that correlates strongly with stand attributes collected at plot level have to be found. Thus, the method is capable for large area forest inventory. By improving the quality of remote sensing data sources, by taking into account airborne data acquisitions, the accuracy of remote sensing based estimates can be improved. Despite this, the accuracy required in standwise forest inventory (about 15% error tolerated, R. Pxc3xa4ivinen, A Pussinen, and E. Tomppo, 1993, xe2x80x9cAssessment of boreal forest stands using field assessment and remote sensingxe2x80x9d, Proceedings of Earsel 1993 Conference xe2x80x9cOperationalization of Remote Sensingxe2x80x9d, ITC Enshedene, The Netherlands, 19-23 Apr., 1993, 8p.) has not been obtained by the use of remote sensing methods.
As an example, the standwise forest inventory in Finland by forestry organizations is performed totally by field work and the national forest inventory is carried out with the help of satellite imagery (such as using Landsat TM images with 30 m spatial resolution). A rather extensive description of accuracy obtained with various remote sensing data sources are depicted in the publications (J. Hyyppxc3xa4, Hyyppxc3xa4, H., Inkinen, M., Engdahl, M., Linko, S. and Zhu, Y-H., 1998. Accuracy of different remote sensing data sources in the retrieval of forest stand attributes. Proceedings of the First International Conference on Geospatial Information in Agriculture and Forestry. Lake Buena Vista, Fla., USA, 1-3 Jun. 1998, Volume I, pp. 370377, and J. Hyyppxc3xa4, Hyyppxc3xa4, H., Inkinen, M, Engdahl, M., Linko, S., Zhu, Y-H., 1999a, Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes, Journal of Forest Ecology and Management (in press)). The applicant of this patent proposal does not know any remote sensing-based forest inventory method that would satisfy the accuracy requirements of standwise forest inventory;
Another type of a method for stem attribute estimation of a forest plot is depicted in the Finnish patent 101016 B. The method registers optically all trees within a defined radius from a selected center. You can e.g. use the AccuRange 3000-LIR laser rangefinder, the accuracy of which is one 65535th of 360xc2x0 or a pulse detector. The registration is carried out by a rotation measurement unit in such a way that the tangent is calculated as the difference in the absolute angular rotation from the discontinuity parts occurring at both sides of the stems. The method (Finnish patent 101016 B) can be used to automate conventional collection of plotwise data but it requires work done in forest and it is rather slow (one rotation takes 1 to 6 minutes, so that the computer would have time to transfer the measurement data). The method is also inventory based on diameter measurements at horizontal level. The major problem with the method depicted in Fl patent 101016 B is that it is so slow that it is suitable only for collecting small amounts of sample from the whole stand.
Previously, aircraft and helicopters have been used to measure forest canopy height with lasers and microwave radars. These earlier measurements were based on measurements of cross-sectional areas of forests (along the flight direction, the height of the stand was measured from the area illuminated with the laser or the radar). Examples of such studies are e.g. R. Nelson, Krabill, W. B., and Maclean, G. A. 1984, xe2x80x9cDetermining forest canopy characteristics using airborne laser dataxe2x80x9d, Remote Sensing Environment, 15:201-212, and J. Hyyppxc3xa4, Hallikainen, M., 1996. Applicability of airborne profiling radar to forest inventory. Remote Sensing Environment, 57: 39-57. Individual trees were not analyzed in these studies, since the images were two-dimensional cross-sections. With these measurements, the tree height was obtained and other attributes derived from that by using regression formulas. The volume estimation errors were at the best about 26.5%, which is not enough for operational use.
Nxc3xa4sset (e.g. E. Nxc3xa4sset, xe2x80x9cDetermination of mean tree height of forest stands using airborne laser scanner dataxe2x80x9d, ISPR J. Photogramm. Remote Sensing, 52, pp. 49-56, 1997.) was able to produce equally distributed samples from the forest using laser scanning, but the estimation of stand characteristics was performed by using statistical methods in a similar way as the previous profiling measurements. As an example, the mean tree height estimate was calculated by taking minimum and maximum heights of laser data within a certain window size.
In year 1999, Hyyppxc3xa4 et al. (J. Hyyppxc3xa4, Hyyppxc3xa4, H., Samberg, A., 1999, Assessing Forest Stand Attributes by Laser Scanner, Laser Radar Technology and Applications IV, Proceedings of SPIE, 3707, 57-69.) demonstrated that it is possible to measure the height of dominant trees by using high pulse rate laser scanner. In this study, volume estimation based on height samples was tested by using a similar approach as previous profiling measurements conducted with lasers and radars. Additionally, a virtual reality tree height model produced with laser scanner was presented in this study. In this work, individual trees were not segmented or recognized and neither any other stand attributes or individual trees.
Also Gunilla Borgefors et al. (Gunilla Borgefors, Tomas Brandberg, Fredrik Walter xe2x80x9cForest parameter extraction from airborne sensorsxe2x80x9d, APRS, Vol.32, Part3-2WS, xe2x80x9cAutomatic Extraction of GIS Objects from Digital Imagingxe2x80x9d, Mxc3xcnchen 8-10 Sep. 1999, pp. 151-158) have proposed the use of laser data for stand attribute retrieval. In the publication, the stem number and the crown size is defined from an image obtained by means of laser data by analyzing the height differences of different areas appearing in the image to a certain reference. The real heights of individual trees mere not analyzed in the publication.
Laser scanning and radar technology have also been generally used for the creation of terrain models by measuring, from above, the distance between a target and a radar (henceforth radar is used as a general name for both the laser and the microwave radar) on the basis of the transmission time of the pulse. Laser radar is also called lidar (light detection and ranging). In such measurements, the laser scanner sweeps the laser pulse formed by the radar across the flight line perpendicularly to the flight line. In this way, the whole target area is covered. Almost adjacent beams are obtained (each beam is typically about a couple of tens of cm in diameter) from the area, and for each beam x, y, and z coordinates are obtained. By analyzing these points, we can calculate various kinds of digital terrain models. A microwave radar operates with a similar principle as the laser radar, the frequency of the transmitted signal is, however, in the microwave region. With microwave radars, the scanning can be performed by using electrical or mechanical scanning mechanisms. A typical beam size on the ground surface produced by the microwave radar is several meters; on the other hand, SAR technology (Synthetic Aperture Radar) can be used to improve the spatial resolution of microwave radar. With microwave radar you can simultaneously measure the distance from both the crown and the ground, why the production of various kinds of terrain models is simpler; on the other hand, it is more difficult to obtain the same spatial resolution as with present and future laser scanners, which are capable to almost 100 kHz pulse repetition rates. This gives an opportunity to record the target with even 0.5 m spatial resolution.
The object of this invention is to develop a remote sensing-based method for forest inventory and retrieval of stand attributes, a method which is faster, more accurate than previous remote sensing-based methods, and which gives better possibilities for further data handling, and which is relatively cost-effective.
The method of the invention for stand attribute retrieval by using a measurement sensor above the stand is mainly characterized in that three-dimensional information is collected from the stand by using such a large number of samples that individual trees or groups of trees can be discriminated. The collected information is used to produce a three-dimensional tree height model of the forest. From the height model, stand attributes are derived. Stand attributesxe2x80x94which are characteristics of individual trees or group of trees and/or characteristics derived using this information for larger areasxe2x80x94are determined from the tree height model
The determination of the stand attributes is preferably carried out in three phases in the invention
1) Construction of a high-resolution three-dimensional measurement from the stand area.
2) Calculation of a three-dimensional tree height model from the measurement data.
3) Determination of stand attributes from the three-dimensional tree height model by using individual trees and groups of trees.
The second and third steps of the method of the invention can be performed by means of a computer program.
In this document, high-resolution refers to a data set capable to discriminate individual trees.
In the boreal forest zone in the Northern Hemisphere and in many economically exploited forest areas and in other forest areas, there exist gaps between the tree crowns. For example, in a thick forest in Finland, more than 30% of the laser pulses are, however, reflected from the ground. By significantly increasing the laser pulse rate (number of pulses sent per second), samples can be obtained from each individual tree crown and also from the ground between the trees. This means that several laser pulses must be recorded per m2 . This allows creation of high-resolution stand maps from laser scanner data. When this material is processed, a terrain model and a crown model can be calculated, as well as the difference between these, in other words a tree height model. By analyzing the tree height model by using e.g. pattern recognition methods, it is possible to locate individual trees, determine individual tree heights, crown diameters, tree species and, by using that data, to derive the stem diameter, number of stems, age, development class, basal area and stem volume for each individual tree. Corresponding information divided into tree species categories can be calculated for sample plots and stands. It is also depicted in the invention how old stand information and knowledge (knowledge-based systems) can be used to improve the accuracy of the stand attributes to be estimated.
The method depicted in the invention is so far the most accurate remote sensing-based forest inventory method of all such methods. The advantage of the invention over typical remote sensing-based methods is that the invented method measures clear physical characteristics from the target in the form of distance data. By using generally known formulas, these parameters can be used to derive stand attributes, such as the volume. Thus, the method does not necessarily require the use of sample plots as teaching material, which reduces the costs of the method.
A high-resolution three-dimensional image is a pre-requisite for the use of the method. The density of the measurements (referring to the distance between the near-by pulses on the ground) influence strongly on the usability of the laser-derived data set. In the invention it has been understood to take the benefits of the increased pulse repetition rates of the laser scanners in a method, which is more recognition-based (several pulses per square meter are obtained, whereby the derivation of several target features begin to appear) than the present state of art methods, which use pure statistical methods. The increases in pulse rate in a way according to the invention gives considerable advantage to forest inventory. High pulse rate enables high spatial resolution and, thus, it is possible to determine characteristics of individual trees. Previously, it has not been possible to produce images, which are capable to discriminate individual trees and to accurately derive such attributes of individual trees, that can be used to calculate, e.g., the volume.
The invented method is generally capable to produce volume estimates for forest stands with errors less than 15% in the boreal forest zone. The method is applicable also elsewhere, especially in plantation forests in the Tropics. This has enabled the generation of a tree map of the forest stand seen from above and because the map is directly in the digital form and because most of the forest information is nowadays recorded in geographical information systems, it is even possible to monitor individual areas and update the treatments to be done even by individual trees. This can be necessary, e.g. in parks and other valuable areas. The cost-efficiency of the method will be continuously improved by the rapid development of laser scanning and radar technology. Full automation (processing of the collected information by means of a computer) is also possible.
In the following, the invention is presented in detail by using figures and examples, which are not meant to restrict the invention by any means.